class_docstr: HuggingFace Text Generation Inference LLM
     Generates text using HuggingFace inference API.
  
  Attributes:
      max_new_tokens: Max number of tokens to generate.
      top_k: Sample from top k tokens.
      top_p: Sample from top p probability.
      typical_p: typical probability of a token.
      temperature: Controls randomness in the model. Lower values will make the model more deterministic and higher values will make the model more random.
      repetition_penalty: controls the likelihood of repeating same tokens based on value.
      truncate: truncate the input to the maximum length of the model.
      stop_sequences: A stop sequence is a string that stops the model from generating tokens.
      seed: The seed to use for random generation.
      do_sample: Whether or not to use sampling.
      timeout: adding timeout restricts huggingface from waiting indefinitely for model's response.
code: def __init__(self, inference_server_url: str, **kwargs):
      try:
          import text_generation
  
          for key, val in kwargs.items():
              if key in self.__annotations__:
                  setattr(self, key, val)
  
          self.client = text_generation.Client(
              base_url=inference_server_url,
              timeout=self.timeout,
          )
  
      except ImportError as e:
          raise ImportError(
              "Could not import text_generation python package. "
              "Please install it with `pip install text_generation`."
          ) from e
  
file_path: pandas-ai/pandasai/llm/huggingface_text_gen.py
imports: from typing import Optional, Any, List, Dict
  from .base import LLM
  from ..helpers import load_dotenv
  from ..prompts.base import AbstractPrompt
label_desc: Use image node_id 1 to create a new HuggingFaceTextGen object from inherited base classes: LLM with example: obj = HuggingFaceTextGen(inference_server_url)